PathoGenSurveil - building dynamic workflows towards a sustainable and efficient genomics-informed pathogen surveillance

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Candida auris in Intensive Care Setting: The First Case Reported in Portugal

Publication . Henriques, João; Mixão, Verónica; Cabrita, Joana; Duarte, Tiago Isidoro; Sequeira, Tânia; Cardoso, Sofia; Germano, Nuno; Dias, Liliana; Bento, Luís; Duarte, Sílvia; Veríssimo, Cristina; Gomes, João Paulo; Sabino, Raquel

Candida auris is an opportunistic human pathogen that has rapidly spread to multiple countries and continents and has been associated with a high number of nosocomial outbreaks. Herein, we report the first case of C. auris in Portugal, which was associated with a patient transferred from Angola to an ICU in Portugal for liver transplantation after a SARS-CoV-2 infection. C. auris was isolated during the course of bronchoalveolar lavage, and it was subjected to antifungal susceptibility testing and whole-genome sequence analysis. This isolate presents low susceptibility to azoles and belongs to the genetic clade III with a phylogenetic placement close to African isolates. Although clade III has already been reported in Europe, taking into account the patient’s clinical history, we cannot discard the possibility that the patient’s colonization/infection occurred in Angola, prior to admission in the Portuguese hospital. Considering that C. auris is a fungal pathogen referenced by WHO as a critical priority, this case reinforces the need for continuous surveillance in a hospital setting

2023-08-09Journal article

Open access

ReporTree: a surveillance-oriented tool to strengthen the linkage between pathogen genetic clusters and epidemiological data

Publication . Mixão, Verónica; Pinto, Miguel; Sobral, Daniel; Di Pasquale, Adriano; Gomes, João Paulo; Borges, Vítor

Background: Genomics-informed pathogen surveillance strengthens public health decision-making, playing an important role in infectious diseases' prevention and control. A pivotal outcome of genomics surveillance is the identification of pathogen genetic clusters and their characterization in terms of geotemporal spread or linkage to clinical and demographic data. This task often consists of the visual exploration of (large) phylogenetic trees and associated metadata, being time-consuming and difficult to reproduce. Results: We developed ReporTree, a flexible bioinformatics pipeline that allows diving into the complexity of pathogen diversity to rapidly identify genetic clusters at any (or all) distance threshold(s) or cluster stability regions and to generate surveillance-oriented reports based on the available metadata, such as timespan, geography, or vaccination/clinical status. ReporTree is able to maintain cluster nomenclature in subsequent analyses and to generate a nomenclature code combining cluster information at different hierarchical levels, thus facilitating the active surveillance of clusters of interest. By handling several input formats and clustering methods, ReporTree is applicable to multiple pathogens, constituting a flexible resource that can be smoothly deployed in routine surveillance bioinformatics workflows with negligible computational and time costs. This is demonstrated through a comprehensive benchmarking of (i) the cg/wgMLST workflow with large datasets of four foodborne bacterial pathogens and (ii) the alignment-based SNP workflow with a large dataset of Mycobacterium tuberculosis. To further validate this tool, we reproduced a previous large-scale study on Neisseria gonorrhoeae, demonstrating how ReporTree is able to rapidly identify the main species genogroups and characterize them with key surveillance metadata, such as antibiotic resistance data. By providing examples for SARS-CoV-2 and the foodborne bacterial pathogen Listeria monocytogenes, we show how this tool is currently a useful asset in genomics-informed routine surveillance and outbreak detection of a wide variety of species. Conclusions: In summary, ReporTree is a pan-pathogen tool for automated and reproducible identification and characterization of genetic clusters that contributes to a sustainable and efficient public health genomics-informed pathogen surveillance. ReporTree is implemented in python 3.8 and is freely available at https://github.com/insapathogenomics/ReporTree .

2023-06-15Journal article

Open access

Multi-country and intersectoral assessment of cluster congruence between pipelines for genomics surveillance of foodborne pathogens

Publication . Mixão, Verónica; Pinto, Miguel; Brendebach, Holger; Sobral, Daniel; Santos, João Dourado; Radomski, Nicolas; Uldall, Anne Sophie Majgaard; Bomba, Arkadiusz; Pietsch, Michael; Bucciacchio, Andrea; de Ruvo, Andrea; Castelli, Pierluigi; Iwan, Ewelina; Simon, Sandra; Coipan, Claudia E.; Linde, Jörg; Petrovska, Liljana; Kaas, Rolf Sommer; Joensen, Katrine Grimstrup; Nielsen, Sofie Holtsmark; Kiil, Kristoffer; Lagesen, Karin; Di Pasquale, Adriano; Gomes, João Paulo; Deneke, Carlus; Tausch, Simon H.; Borges, Vítor

Different laboratories employ different Whole-Genome Sequencing (WGS) pipelines for Food and Waterborne disease (FWD) surveillance, casting doubt on the comparability of their results and hindering optimal communication at intersectoral and international levels. Through a collaborative effort involving eleven European institutes spanning the food, animal, and human health sectors, we aimed to assess the inter-pipeline clustering congruence across all resolution levels and perform an in-depth comparative analysis of cluster composition at outbreak level for four important foodborne pathogens: Listeria monocytogenes, Salmonella enterica, Escherichia coli, and Campylobacter jejuni. We found a general concordance between allele-based pipelines for all species, except for C. jejuni, where the different resolution power of allele-based schemas led to marked discrepancies. Still, we identified non-negligible differences in outbreak detection and demonstrated how a threshold flexibilization favors the detection of similar outbreak signals by different laboratories. These results, together with the observation that different traditional typing groups (e.g., serotypes) exhibit a remarkably different genetic diversity, represent valuable information for future outbreak case-definitions and WGS-based nomenclature design. This study reinforces the need, while demonstrating the feasibility, of conducting continuous pipeline comparability assessments, and opens good perspectives for a smoother international and intersectoral cooperation towards an efficient One Health FWD surveillance.

2025-04-28Journal article

Open access